Multidimensional Analysis of the Role of Charged Multivesicular Body Protein 7 in Pan-Cancer

Transcriptional immune suppression and up-regulation of double-stranded DNA damage and repair repertoires in ecDNA-containing tumors

Extrachromosomal DNA is a common cause of oncogene amplification in cancer. The non-chromosomal inheritance of ecDNA enables tumors to rapidly evolve, contributing to treatment resistance and poor outcome for patients. The transcriptional context in which ecDNAs arise and progress, including chromosomally-driven transcription, is incompletely understood. We examined gene expression patterns of 870 tumors of varied histological types, to identify transcriptional correlates of ecDNA. Here, we show that ecDNA-containing tumors impact four major biological processes. Specifically, ecDNA-containing tumors up-regulate DNA damage and repair, cell cycle control, and mitotic processes, but down-regulate global immune regulation pathways. Taken together, these results suggest profound alterations in gene regulation in ecDNA-containing tumors, shedding light on molecular processes that give rise to their development and progression.

Relevance of pyroptosis-associated genes in nasopharyngeal carcinoma diagnosis and subtype classification

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a highly aggressive and metastatic malignancy originating in the nasopharyngeal tissue. Pyroptosis is a relatively newly discovered, regulated form of necrotic cell death induced by inflammatory caspases that is associated with a variety of diseases. However, the role and mechanism of pyroptosis in NPC are not fully understood.

METHODS

We analyzed the differential expression of pyroptosis-related genes (PRGs) between patients with and without NPC from the GSE53819 and GSE64634 datasets of the Gene Expression Omnibus (GEO) database. We mapped receptor operating characteristic profiles for these key PRGs to assess the accuracy of the genes for disease diagnosis and prediction of patient prognosis. In addition, we constructed a nomogram based on these key PRGs and carried out a decision curve analysis. The NPC patients were classified into different pyroptosis gene clusters by the consensus clustering method based on key PRGs, whereas the expression profiles of the key PRGs were analyzed by applying principal component analysis. We also analyzed the differences in key PRGs, immune cell infiltration and NPC-related genes between the clusters. Finally, we performed differential expression analysis for pyroptosis clusters and obtained differentially expressed genes (DEGs) and performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses.

RESULTS

We obtained 14 differentially expressed PRGs from GEO database. Based on these 14 differentially expressed PRGs, we applied least absolute shrinkage and selection operator analysis and the random forest algorithm to obtain four key PRGs (CHMP7, IL1A, TP63 and GSDMB). We completely distinguished the NPC patients into two pyroptosis gene clusters (pyroptosis clusters A and B) based on four key PRGs. Furthermore, we determined the immune cell abundance of each NPC sample, estimated the association between the four PRGs and immune cells, and determined the difference in immune cell infiltration between the two pyroptosis gene clusters. Finally, we obtained and functional enrichment analyses 259 DEGs by differential expression analysis for both pyroptosis clusters.

CONCLUSIONS

PRGs are critical in the development of NPC, and our research on the pyroptosis gene cluster may help direct future NPC therapeutic approaches.

Transcriptional immune suppression and upregulation of double stranded DNA damage and repair repertoires in ecDNA-containing tumors

Extrachromosomal DNA is a common cause of oncogene amplification in cancer. The non-chromosomal inheritance of ecDNA enables tumors to rapidly evolve, contributing to treatment resistance and poor outcome for patients. The transcriptional context in which ecDNAs arise and progress, including chromosomally-driven transcription, is incompletely understood. We examined gene expression patterns of 870 tumors of varied histological types, to identify transcriptional correlates of ecDNA. Here we show that ecDNA containing tumors impact four major biological processes. Specifically, ecDNA containing tumors upregulate DNA damage and repair, cell cycle control, and mitotic processes, but downregulate global immune regulation pathways. Taken together, these results suggest profound alterations in gene regulation in ecDNA containing tumors, shedding light on molecular processes that give rise to their development and progression.

Development and validation of a novel necroptosis-related gene signature for predicting prognosis and therapeutic response in Ewing sarcoma

Ewing sarcoma (ES) is the second most common malignant bone tumor in children and has a poor prognosis due to early metastasis and easy recurrence. Necroptosis is a newly discovered cell death method, and its critical role in tumor immunity and therapy has attracted widespread attention. Thus, the emergence of necroptosis may provide bright prospects for the treatment of ES and deserves our further study. Here, based on the random forest algorithm, we identified 6 key necroptosis-related genes (NRGs) and used them to construct an NRG signature with excellent predictive performance. Subsequent analysis showed that NRGs were closely associated with ES tumor immunity, and the signature was also good at predicting immunotherapy and chemotherapy response. Next, a comprehensive analysis of key genes showed that RIPK1, JAK1, and CHMP7 were potential therapeutic targets. The Cancer Dependency Map (DepMap) results showed that CHMP7 is associated with ES cell growth, and the Gene Set Cancer Analysis (GSCALite) results revealed that the JAK1 mutation frequency was the highest. The expression of 3 genes was all negatively correlated with methylation and positively with copy number variation (CNV). Finally, an accurate nomogram was constructed with this signature and clinical traits. In short, this study constructed an accurate prognostic signature and identified 3 novel therapeutic targets against ES.

Development of a prognostic prediction model based on a combined multi-omics analysis of head and neck squamous cell carcinoma cell pyroptosis-related genes

This study aimed to understand the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) and to develop and validate a prognostic model for HNSCC based on pyroptosis-associated genes (PAGs) in nasopharyngeal carcinoma. The Cancer Genome Atlas database was used to identify differentially expressed PAGs. These genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes functional annotation analyses and Gene Ontology analyses. The NLR family pyrin domain containing 1 (NLRP1) gene, charged multivesicular body protein 7 (CHMP7) gene, and cytochrome C (CYCS) gene were used to create a prognostic model for HNSCC. The results of the Kaplan-Meier (K-M) and Cox regression analyses indicated that the developed model served as an independent risk factor for HNSCC. According to the K-M analysis, the overall survival of high-risk patients was lower than that of low-risk patients. The hazard ratios corresponding to the risk scores determined using the multivariate and univariate Cox regression analyses were 1.646 (95% confidence interval (CI): 1.189–2.278) and 1.724 (95% CI: 1.294–2.298), respectively, and the area under the receiver operator characteristic curve was 0.621. The potential mechanisms associated with the functions of the identified genes were then identified, and the tumor microenvironment and levels of immune cell infiltration achieved were analyzed. The immune infiltration analysis revealed differences in the distribution of Th cells, tumor-infiltrating lymphocytes, regulatory T cells, follicular helper T cells, adipose-derived cells, interdigitating dendritic cells, CD8⁺ T cells, and B cells. However, validating bioinformatics analyses through biological experiments is still recommended. This study developed a prognostic model for HNSCC that included NLRP1, CHMP7, and CYCS.

Necroptosis-Related Genes Associated With Immune Activity and Prognosis of Colorectal Cancer

This study aims at screening out the key necroptosis-related genes in colorectal cancer and elucidating the role of necroptosis-related genes in the immune activity and prognosis of colorectal cancer (CRC). The CRC patients’ data were downloaded from The Cancer Genome Atlas (TCGA). The non-negative matrix factorization method was applied to identify new molecular subgroups. Survival analysis and single sample Gene Set Enrichment Analysis were performed to determinate the differences in the overall survival time and immune status of the subgroups. Prognostic model was constructed on the basis of univariate Cox regression and LASSO analysis. Functional analyses were used to explore the potential mechanisms. Based on prognostic related necroptosis genes, we identify two molecular subgroups with significantly different survival. The better prognosis was associated with more active immune infiltration and upregulated expression of immune checkpoints. We screened nine necroptosis related genes as key prognostic genes and established a risk model, which showed a good potential for survival prediction in colorectal cancer. Nomogram assessment showed that the model had high reliability for predicting the prognosis of colorectal cancer patients. The high-risk and low-risk group also has different sensitivity to immunotherapy and commonly used drugs for colorectal cancer. Overall, necroptosis related genes were involved in the immune microenvironment of colorectal cancer patient, could be utilized to predict the prognosis of colorectal cancer and develop more individualized treatment.

Integrative Analysis of a Pyroptosis-Related Signature of Clinical and Biological Value in Multiple Myeloma

Purpose

Pyroptosis is an inflammation-based programmed cell death that holds great potential as a novel cancer therapeutic target in patients with multiple myeloma (MM). However, thus far, the function of pyroptosis-related genes (PRGs) in MM and their prognostic relevance remains undetermined.

Methods

The model was established by the LASSO analysis, based on the Gene Expression Omnibus (GEO) dabatase, and its efficacy was verified using two external datasets. The model’s predictive ability was assessed by the Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) curves. Finally, a nomogram was established for clinical application. We also confirmed the validity of our model using specimens and in vitro experiments.

Results

We established an 11-PRG signature profile, and verified its efficacy using two validation cohorts (VCs). In both cohorts, patients were separated into two subpopulations, according to their median risk scores (RS). Our analysis revealed that high-risk (HR) patients experienced considerably lower overall survival (OS), compared to the low-risk (LR) patients. Using functional enrichment and immune infiltration analyses, we demonstrated that the immunologic status was strongly related to RS. Furthermore, using a pyroptosis inhibitor Q-VD-OPh, we revealed that MM cell proliferation and progression was drastically suppressed and the doxorubicin (DOX)-induced apoptosis was reversed.

Conclusion

Based on our analysis, pyroptosis not only serves as a measure of MM treatment efficiency and patient prognosis, but is also a possible target for anti-MM therapy.